Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

Patronus AI unveiled “Generative Simulators,” adaptive “practice worlds” that replace static benchmarks with dynamic reinforcement-learning environments to train more reliable AI agents for complex, ...

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

AI guys love talking about “vibes.” There’s “vibe coding,” a term coined by OpenAI co-founder Andrej Karpathy to describe ...

AI bots told to act as trading agents in simulated markets engaged in pervasive collusion, raising new questions about how ...

The rise of the AI gig workforce has driven an important shift from commodity task execution to first-tier crowd contribution ...